From 948bf6d0693bfecbaf1a4aa60bf539d84380b36a Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <patrick_hoefler@gmx.net>
Date: Thu, 2 Feb 2023 18:59:42 +0100
Subject: [PATCH 1/5] DOC: remove inplace usage from docstring examples

---
 pandas/core/arrays/categorical.py |  7 -----
 pandas/core/frame.py              | 18 ------------
 pandas/core/indexes/base.py       |  7 -----
 pandas/core/series.py             | 46 ++-----------------------------
 4 files changed, 2 insertions(+), 76 deletions(-)

diff --git a/pandas/core/arrays/categorical.py b/pandas/core/arrays/categorical.py
index f2e54185c11ff..7197994bfbcb1 100644
--- a/pandas/core/arrays/categorical.py
+++ b/pandas/core/arrays/categorical.py
@@ -1673,13 +1673,6 @@ def sort_values(
         [5, 2, 2, 1, 1]
         Categories (3, int64): [1, 2, 5]
 
-        Inplace sorting can be done as well:
-
-        >>> c.sort_values(inplace=True)
-        >>> c
-        [1, 1, 2, 2, 5]
-        Categories (3, int64): [1, 2, 5]
-        >>>
         >>> c = pd.Categorical([1, 2, 2, 1, 5])
 
         'sort_values' behaviour with NaNs. Note that 'na_position'
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 36a7ef7cd6d9e..44550169f1f20 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4512,17 +4512,6 @@ def eval(self, expr: str, *, inplace: bool = False, **kwargs) -> Any | None:
         3  4   4
         4  5   2
 
-        Use ``inplace=True`` to modify the original DataFrame.
-
-        >>> df.eval('C = A + B', inplace=True)
-        >>> df
-           A   B   C
-        0  1  10  11
-        1  2   8  10
-        2  3   6   9
-        3  4   4   8
-        4  5   2   7
-
         Multiple columns can be assigned to using multi-line expressions:
 
         >>> df.eval(
@@ -6372,13 +6361,6 @@ def dropna(
                name        toy       born
         1    Batman  Batmobile 1940-04-25
         2  Catwoman   Bullwhip        NaT
-
-        Keep the DataFrame with valid entries in the same variable.
-
-        >>> df.dropna(inplace=True)
-        >>> df
-             name        toy       born
-        1  Batman  Batmobile 1940-04-25
         """
         if (how is not no_default) and (thresh is not no_default):
             raise TypeError(
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 881e83313ced5..40e6a593678da 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1745,13 +1745,6 @@ def set_names(
                     ( 'cobra', 2018),
                     ( 'cobra', 2019)],
                    )
-        >>> idx.set_names(['kind', 'year'], inplace=True)
-        >>> idx
-        MultiIndex([('python', 2018),
-                    ('python', 2019),
-                    ( 'cobra', 2018),
-                    ( 'cobra', 2019)],
-                   names=['kind', 'year'])
         >>> idx.set_names('species', level=0)
         MultiIndex([('python', 2018),
                     ('python', 2019),
diff --git a/pandas/core/series.py b/pandas/core/series.py
index 63420309f33fc..05c5f18aa1faa 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -1494,17 +1494,6 @@ def reset_index(
         3    4
         Name: foo, dtype: int64
 
-        To update the Series in place, without generating a new one
-        set `inplace` to True. Note that it also requires ``drop=True``.
-
-        >>> s.reset_index(inplace=True, drop=True)
-        >>> s
-        0    1
-        1    2
-        2    3
-        3    4
-        Name: foo, dtype: int64
-
         The `level` parameter is interesting for Series with a multi-level
         index.
 
@@ -2242,11 +2231,9 @@ def drop_duplicates(
         Name: animal, dtype: object
 
         The value ``False`` for parameter 'keep' discards all sets of
-        duplicated entries. Setting the value of 'inplace' to ``True`` performs
-        the operation inplace and returns ``None``.
+        duplicated entries.
 
-        >>> s.drop_duplicates(keep=False, inplace=True)
-        >>> s
+        >>> s.drop_duplicates(keep=False)
         1       cow
         3    beetle
         5     hippo
@@ -3490,17 +3477,6 @@ def sort_values(
         0     NaN
         dtype: float64
 
-        Sort values inplace
-
-        >>> s.sort_values(ascending=False, inplace=True)
-        >>> s
-        3    10.0
-        4     5.0
-        2     3.0
-        1     1.0
-        0     NaN
-        dtype: float64
-
         Sort values putting NAs first
 
         >>> s.sort_values(na_position='first')
@@ -3750,16 +3726,6 @@ def sort_index(
         1    c
         dtype: object
 
-        Sort Inplace
-
-        >>> s.sort_index(inplace=True)
-        >>> s
-        1    c
-        2    b
-        3    a
-        4    d
-        dtype: object
-
         By default NaNs are put at the end, but use `na_position` to place
         them at the beginning
 
@@ -5601,14 +5567,6 @@ def dropna(
         1    2.0
         dtype: float64
 
-        Keep the Series with valid entries in the same variable.
-
-        >>> ser.dropna(inplace=True)
-        >>> ser
-        0    1.0
-        1    2.0
-        dtype: float64
-
         Empty strings are not considered NA values. ``None`` is considered an
         NA value.
 

From 4e5fdb7aabf6fd961565bb1df5b8bb2a00462725 Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <patrick_hoefler@gmx.net>
Date: Thu, 2 Feb 2023 21:25:02 +0100
Subject: [PATCH 2/5] Remove copy examples

---
 pandas/core/frame.py   |  7 -------
 pandas/core/generic.py | 11 -----------
 2 files changed, 18 deletions(-)

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 44550169f1f20..496a69bc1eeba 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4988,13 +4988,6 @@ def align(
         1  2   5
         2  3   6
 
-        Now, update the labels without copying the underlying data.
-
-        >>> df.set_axis(['i', 'ii'], axis='columns', copy=False)
-           i  ii
-        0  1   4
-        1  2   5
-        2  3   6
         """
     )
     @Substitution(
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 8fa86e80e1a44..6211248129ee6 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -6216,17 +6216,6 @@ def astype(
         dtype: category
         Categories (2, int64): [2 < 1]
 
-        Note that using ``copy=False`` and changing data on a new
-        pandas object may propagate changes:
-
-        >>> s1 = pd.Series([1, 2])
-        >>> s2 = s1.astype('int64', copy=False)
-        >>> s2[0] = 10
-        >>> s1  # note that s1[0] has changed too
-        0    10
-        1     2
-        dtype: int64
-
         Create a series of dates:
 
         >>> ser_date = pd.Series(pd.date_range('20200101', periods=3))

From 201f87795bfc281fa5b0663c9c82ef6afffea01e Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <patrick_hoefler@gmx.net>
Date: Thu, 2 Feb 2023 23:14:01 +0100
Subject: [PATCH 3/5] Fix some warnings

---
 pandas/compat/numpy/__init__.py              |  1 +
 pandas/core/arrays/masked.py                 | 13 ++++++++++---
 pandas/core/dtypes/astype.py                 |  5 ++++-
 pandas/core/dtypes/cast.py                   |  4 +++-
 pandas/core/indexes/base.py                  | 12 +++++++++---
 pandas/tests/io/parser/test_c_parser_only.py | 17 ++++++++++-------
 pandas/tests/series/test_constructors.py     |  4 ++--
 7 files changed, 39 insertions(+), 17 deletions(-)

diff --git a/pandas/compat/numpy/__init__.py b/pandas/compat/numpy/__init__.py
index 60ec74553a207..6f31358dabe86 100644
--- a/pandas/compat/numpy/__init__.py
+++ b/pandas/compat/numpy/__init__.py
@@ -9,6 +9,7 @@
 np_version_under1p21 = _nlv < Version("1.21")
 np_version_under1p22 = _nlv < Version("1.22")
 np_version_gte1p22 = _nlv >= Version("1.22")
+np_version_gte1p24 = _nlv >= Version("1.24")
 is_numpy_dev = _nlv.dev is not None
 _min_numpy_ver = "1.20.3"
 
diff --git a/pandas/core/arrays/masked.py b/pandas/core/arrays/masked.py
index 8324d4b2618f1..e38886ebfa16b 100644
--- a/pandas/core/arrays/masked.py
+++ b/pandas/core/arrays/masked.py
@@ -428,10 +428,14 @@ def to_numpy(
                     "for this dtype."
                 )
             # don't pass copy to astype -> always need a copy since we are mutating
-            data = self._data.astype(dtype)
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore")
+                data = self._data.astype(dtype)
             data[self._mask] = na_value
         else:
-            data = self._data.astype(dtype, copy=copy)
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore")
+                data = self._data.astype(dtype, copy=copy)
         return data
 
     @doc(ExtensionArray.tolist)
@@ -464,7 +468,10 @@ def astype(self, dtype: AstypeArg, copy: bool = True) -> ArrayLike:
         # if we are astyping to another nullable masked dtype, we can fastpath
         if isinstance(dtype, BaseMaskedDtype):
             # TODO deal with NaNs for FloatingArray case
-            data = self._data.astype(dtype.numpy_dtype, copy=copy)
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore")
+                # TODO: Is rounding what we want long term?
+                data = self._data.astype(dtype.numpy_dtype, copy=copy)
             # mask is copied depending on whether the data was copied, and
             # not directly depending on the `copy` keyword
             mask = self._mask if data is self._data else self._mask.copy()
diff --git a/pandas/core/dtypes/astype.py b/pandas/core/dtypes/astype.py
index e5b0b5658534f..59828ea9bb823 100644
--- a/pandas/core/dtypes/astype.py
+++ b/pandas/core/dtypes/astype.py
@@ -9,6 +9,7 @@
     TYPE_CHECKING,
     overload,
 )
+import warnings
 
 import numpy as np
 
@@ -153,7 +154,9 @@ def _astype_float_to_int_nansafe(
         # GH#45151
         if not (values >= 0).all():
             raise ValueError(f"Cannot losslessly cast from {values.dtype} to {dtype}")
-    return values.astype(dtype, copy=copy)
+    with warnings.catch_warnings():
+        warnings.filterwarnings("ignore")
+        return values.astype(dtype, copy=copy)
 
 
 def astype_array(values: ArrayLike, dtype: DtypeObj, copy: bool = False) -> ArrayLike:
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 3be89f6da2bd8..14b57a5f4642c 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -1606,7 +1606,9 @@ def maybe_cast_to_integer_array(arr: list | np.ndarray, dtype: np.dtype) -> np.n
                 )
                 casted = np.array(arr, dtype=dtype, copy=False)
         else:
-            casted = arr.astype(dtype, copy=False)
+            with warnings.catch_warnings():
+                warnings.filterwarnings("ignore")
+                casted = arr.astype(dtype, copy=False)
     except OverflowError as err:
         raise OverflowError(
             "The elements provided in the data cannot all be "
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 13afd6e5be664..efc35d2175b4f 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -3874,9 +3874,15 @@ def _get_fill_indexer(
             #  but that doesn't appear to be enforced
             # error: "IndexEngine" has no attribute "get_indexer_with_fill"
             engine = self._engine
-            return engine.get_indexer_with_fill(  # type: ignore[union-attr]
-                target=target._values, values=self._values, method=method, limit=limit
-            )
+            with warnings.catch_warnings():
+                # TODO: We need to fix this. Casting to int64 in cython
+                warnings.filterwarnings("ignore")
+                return engine.get_indexer_with_fill(  # type: ignore[union-attr]
+                    target=target._values,
+                    values=self._values,
+                    method=method,
+                    limit=limit,
+                )
 
         if self.is_monotonic_increasing and target.is_monotonic_increasing:
             target_values = target._get_engine_target()
diff --git a/pandas/tests/io/parser/test_c_parser_only.py b/pandas/tests/io/parser/test_c_parser_only.py
index d5a7610ecb8a9..4c6bc3583676a 100644
--- a/pandas/tests/io/parser/test_c_parser_only.py
+++ b/pandas/tests/io/parser/test_c_parser_only.py
@@ -21,6 +21,7 @@
     IS64,
     is_ci_environment,
 )
+from pandas.compat.numpy import np_version_gte1p24
 from pandas.errors import ParserError
 import pandas.util._test_decorators as td
 
@@ -114,14 +115,16 @@ def test_dtype_and_names_error(c_parser_only):
 3.0 3
 """
     # fallback casting, but not castable
+    warning = RuntimeWarning if np_version_gte1p24 else None
     with pytest.raises(ValueError, match="cannot safely convert"):
-        parser.read_csv(
-            StringIO(data),
-            sep=r"\s+",
-            header=None,
-            names=["a", "b"],
-            dtype={"a": np.int32},
-        )
+        with tm.assert_produces_warning(warning, check_stacklevel=False):
+            parser.read_csv(
+                StringIO(data),
+                sep=r"\s+",
+                header=None,
+                names=["a", "b"],
+                dtype={"a": np.int32},
+            )
 
 
 @pytest.mark.parametrize(
diff --git a/pandas/tests/series/test_constructors.py b/pandas/tests/series/test_constructors.py
index 7f65bce873126..99f7f06b2fc89 100644
--- a/pandas/tests/series/test_constructors.py
+++ b/pandas/tests/series/test_constructors.py
@@ -798,7 +798,7 @@ def test_constructor_floating_data_int_dtype(self, frame_or_series):
         # Long-standing behavior (for Series, new in 2.0 for DataFrame)
         #  has been to ignore the dtype on these;
         #  not clear if this is what we want long-term
-        expected = frame_or_series(arr)
+        # expected = frame_or_series(arr)
 
         # GH#49599 as of 2.0 we raise instead of silently retaining float dtype
         msg = "Trying to coerce float values to integer"
@@ -810,7 +810,7 @@ def test_constructor_floating_data_int_dtype(self, frame_or_series):
 
         # pre-2.0, when we had NaNs, we silently ignored the integer dtype
         arr[0] = np.nan
-        expected = frame_or_series(arr)
+        # expected = frame_or_series(arr)
 
         msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
         with pytest.raises(IntCastingNaNError, match=msg):

From ce3c59010c292a851fb343b767ba2595e31a9266 Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <patrick_hoefler@gmx.net>
Date: Fri, 3 Feb 2023 10:26:16 +0100
Subject: [PATCH 4/5] Fix docstring

---
 pandas/core/frame.py        | 1 -
 pandas/core/indexes/base.py | 1 +
 2 files changed, 1 insertion(+), 1 deletion(-)

diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 496a69bc1eeba..4f13ead4005e7 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -4987,7 +4987,6 @@ def align(
         0  1   4
         1  2   5
         2  3   6
-
         """
     )
     @Substitution(
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index efc35d2175b4f..92217b940c11c 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1745,6 +1745,7 @@ def set_names(
                     ( 'cobra', 2018),
                     ( 'cobra', 2019)],
                    )
+        >>> idx = idx.set_names(['kind', 'year'])
         >>> idx.set_names('species', level=0)
         MultiIndex([('python', 2018),
                     ('python', 2019),

From dc7b0280bbe867563536ed2a03be5545159a52fd Mon Sep 17 00:00:00 2001
From: Patrick Hoefler <patrick_hoefler@gmx.net>
Date: Fri, 3 Feb 2023 10:26:58 +0100
Subject: [PATCH 5/5] Revert "Fix some warnings"

This reverts commit 201f87795bfc281fa5b0663c9c82ef6afffea01e.
---
 pandas/compat/numpy/__init__.py              |  1 -
 pandas/core/arrays/masked.py                 | 13 +++----------
 pandas/core/dtypes/astype.py                 |  5 +----
 pandas/core/dtypes/cast.py                   |  4 +---
 pandas/core/indexes/base.py                  | 12 +++---------
 pandas/tests/io/parser/test_c_parser_only.py | 17 +++++++----------
 pandas/tests/series/test_constructors.py     |  4 ++--
 7 files changed, 17 insertions(+), 39 deletions(-)

diff --git a/pandas/compat/numpy/__init__.py b/pandas/compat/numpy/__init__.py
index 6f31358dabe86..60ec74553a207 100644
--- a/pandas/compat/numpy/__init__.py
+++ b/pandas/compat/numpy/__init__.py
@@ -9,7 +9,6 @@
 np_version_under1p21 = _nlv < Version("1.21")
 np_version_under1p22 = _nlv < Version("1.22")
 np_version_gte1p22 = _nlv >= Version("1.22")
-np_version_gte1p24 = _nlv >= Version("1.24")
 is_numpy_dev = _nlv.dev is not None
 _min_numpy_ver = "1.20.3"
 
diff --git a/pandas/core/arrays/masked.py b/pandas/core/arrays/masked.py
index e38886ebfa16b..8324d4b2618f1 100644
--- a/pandas/core/arrays/masked.py
+++ b/pandas/core/arrays/masked.py
@@ -428,14 +428,10 @@ def to_numpy(
                     "for this dtype."
                 )
             # don't pass copy to astype -> always need a copy since we are mutating
-            with warnings.catch_warnings():
-                warnings.filterwarnings("ignore")
-                data = self._data.astype(dtype)
+            data = self._data.astype(dtype)
             data[self._mask] = na_value
         else:
-            with warnings.catch_warnings():
-                warnings.filterwarnings("ignore")
-                data = self._data.astype(dtype, copy=copy)
+            data = self._data.astype(dtype, copy=copy)
         return data
 
     @doc(ExtensionArray.tolist)
@@ -468,10 +464,7 @@ def astype(self, dtype: AstypeArg, copy: bool = True) -> ArrayLike:
         # if we are astyping to another nullable masked dtype, we can fastpath
         if isinstance(dtype, BaseMaskedDtype):
             # TODO deal with NaNs for FloatingArray case
-            with warnings.catch_warnings():
-                warnings.filterwarnings("ignore")
-                # TODO: Is rounding what we want long term?
-                data = self._data.astype(dtype.numpy_dtype, copy=copy)
+            data = self._data.astype(dtype.numpy_dtype, copy=copy)
             # mask is copied depending on whether the data was copied, and
             # not directly depending on the `copy` keyword
             mask = self._mask if data is self._data else self._mask.copy()
diff --git a/pandas/core/dtypes/astype.py b/pandas/core/dtypes/astype.py
index 59828ea9bb823..e5b0b5658534f 100644
--- a/pandas/core/dtypes/astype.py
+++ b/pandas/core/dtypes/astype.py
@@ -9,7 +9,6 @@
     TYPE_CHECKING,
     overload,
 )
-import warnings
 
 import numpy as np
 
@@ -154,9 +153,7 @@ def _astype_float_to_int_nansafe(
         # GH#45151
         if not (values >= 0).all():
             raise ValueError(f"Cannot losslessly cast from {values.dtype} to {dtype}")
-    with warnings.catch_warnings():
-        warnings.filterwarnings("ignore")
-        return values.astype(dtype, copy=copy)
+    return values.astype(dtype, copy=copy)
 
 
 def astype_array(values: ArrayLike, dtype: DtypeObj, copy: bool = False) -> ArrayLike:
diff --git a/pandas/core/dtypes/cast.py b/pandas/core/dtypes/cast.py
index 14b57a5f4642c..3be89f6da2bd8 100644
--- a/pandas/core/dtypes/cast.py
+++ b/pandas/core/dtypes/cast.py
@@ -1606,9 +1606,7 @@ def maybe_cast_to_integer_array(arr: list | np.ndarray, dtype: np.dtype) -> np.n
                 )
                 casted = np.array(arr, dtype=dtype, copy=False)
         else:
-            with warnings.catch_warnings():
-                warnings.filterwarnings("ignore")
-                casted = arr.astype(dtype, copy=False)
+            casted = arr.astype(dtype, copy=False)
     except OverflowError as err:
         raise OverflowError(
             "The elements provided in the data cannot all be "
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 92217b940c11c..3eef90343bdf6 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -3875,15 +3875,9 @@ def _get_fill_indexer(
             #  but that doesn't appear to be enforced
             # error: "IndexEngine" has no attribute "get_indexer_with_fill"
             engine = self._engine
-            with warnings.catch_warnings():
-                # TODO: We need to fix this. Casting to int64 in cython
-                warnings.filterwarnings("ignore")
-                return engine.get_indexer_with_fill(  # type: ignore[union-attr]
-                    target=target._values,
-                    values=self._values,
-                    method=method,
-                    limit=limit,
-                )
+            return engine.get_indexer_with_fill(  # type: ignore[union-attr]
+                target=target._values, values=self._values, method=method, limit=limit
+            )
 
         if self.is_monotonic_increasing and target.is_monotonic_increasing:
             target_values = target._get_engine_target()
diff --git a/pandas/tests/io/parser/test_c_parser_only.py b/pandas/tests/io/parser/test_c_parser_only.py
index 4c6bc3583676a..d5a7610ecb8a9 100644
--- a/pandas/tests/io/parser/test_c_parser_only.py
+++ b/pandas/tests/io/parser/test_c_parser_only.py
@@ -21,7 +21,6 @@
     IS64,
     is_ci_environment,
 )
-from pandas.compat.numpy import np_version_gte1p24
 from pandas.errors import ParserError
 import pandas.util._test_decorators as td
 
@@ -115,16 +114,14 @@ def test_dtype_and_names_error(c_parser_only):
 3.0 3
 """
     # fallback casting, but not castable
-    warning = RuntimeWarning if np_version_gte1p24 else None
     with pytest.raises(ValueError, match="cannot safely convert"):
-        with tm.assert_produces_warning(warning, check_stacklevel=False):
-            parser.read_csv(
-                StringIO(data),
-                sep=r"\s+",
-                header=None,
-                names=["a", "b"],
-                dtype={"a": np.int32},
-            )
+        parser.read_csv(
+            StringIO(data),
+            sep=r"\s+",
+            header=None,
+            names=["a", "b"],
+            dtype={"a": np.int32},
+        )
 
 
 @pytest.mark.parametrize(
diff --git a/pandas/tests/series/test_constructors.py b/pandas/tests/series/test_constructors.py
index 99f7f06b2fc89..7f65bce873126 100644
--- a/pandas/tests/series/test_constructors.py
+++ b/pandas/tests/series/test_constructors.py
@@ -798,7 +798,7 @@ def test_constructor_floating_data_int_dtype(self, frame_or_series):
         # Long-standing behavior (for Series, new in 2.0 for DataFrame)
         #  has been to ignore the dtype on these;
         #  not clear if this is what we want long-term
-        # expected = frame_or_series(arr)
+        expected = frame_or_series(arr)
 
         # GH#49599 as of 2.0 we raise instead of silently retaining float dtype
         msg = "Trying to coerce float values to integer"
@@ -810,7 +810,7 @@ def test_constructor_floating_data_int_dtype(self, frame_or_series):
 
         # pre-2.0, when we had NaNs, we silently ignored the integer dtype
         arr[0] = np.nan
-        # expected = frame_or_series(arr)
+        expected = frame_or_series(arr)
 
         msg = r"Cannot convert non-finite values \(NA or inf\) to integer"
         with pytest.raises(IntCastingNaNError, match=msg):